Next Article in Journal
Next Article in Special Issue
Previous Article in Journal
Previous Article in Special Issue
Sensors 2009, 9(3), 2187-2201; doi:10.3390/s90302187
Article

Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks

1,* , 1
, 2
, 3
 and 3
Received: 6 November 2008; in revised form: 18 March 2009 / Accepted: 18 March 2009 / Published: 26 March 2009
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Japan)
View Full-Text   |   Download PDF [1172 KB, uploaded 21 June 2014]   |   Browse Figures
Abstract: This paper proposes a method to quantitatively measure and evaluate finger tapping movements for the assessment of motor function using log-linearized Gaussian mixture networks (LLGMNs). First, finger tapping movements are measured using magnetic sensors, and eleven indices are computed for evaluation. After standardizing these indices based on those of normal subjects, they are input to LLGMNs to assess motor function. Then, motor ability is probabilistically discriminated to determine whether it is normal or not using a classifier combined with the output of multiple LLGMNs based on bagging and entropy. This paper reports on evaluation and discrimination experiments performed on finger tapping movements in 33 Parkinson’s disease (PD) patients and 32 normal elderly subjects. The results showed that the patients could be classified correctly in terms of their impairment status with a high degree of accuracy (average rate: 93:1 § 3:69%) using 12 LLGMNs, which was about 5% higher than the results obtained using a single LLGMN.
Keywords: Finger tapping movements; magnetic sensors; neural networks; pattern discrimination; diagnosis support Finger tapping movements; magnetic sensors; neural networks; pattern discrimination; diagnosis support
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Shima, K.; Tsuji, T.; Kandori, A.; Yokoe, M.; Sakoda, S. Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks. Sensors 2009, 9, 2187-2201.

AMA Style

Shima K, Tsuji T, Kandori A, Yokoe M, Sakoda S. Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks. Sensors. 2009; 9(3):2187-2201.

Chicago/Turabian Style

Shima, Keisuke; Tsuji, Toshio; Kandori, Akihiko; Yokoe, Masaru; Sakoda, Saburo. 2009. "Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks." Sensors 9, no. 3: 2187-2201.



Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert